J Mol Neurosci (2014) 54:739–747 DOI 10.1007/s12031-014-0356-x

Protein-Based Biomarkers in Cerebrospinal Fluid and Blood for Alzheimer’s Disease Yongyao Fu & Deming Zhao & Lifeng Yang

Received: 17 May 2014 / Accepted: 11 June 2014 / Published online: 25 June 2014 # Springer Science+Business Media New York 2014

Abstract Alzheimer’s disease (AD) is a common neurodegenerative disease. Although early diagnosis of AD is challenging, identification and treatment at the preclinical stage is critical for preventing the severe and irreversible damage to neurons. Thus, during the last few decades, many researchers have sought efficient biomarkers for early diagnosis of AD, monitoring disease progression, and gauging responses to therapies. Recently, various molecular markers have been investigated in blood, plasma, cerebrospinal fluid, and other body fluids. This review summarizes the results of some recent studies that searched for biomarkers of AD in cerebrospinal fluid (CSF) and blood. Keyword Alzheimer’s disease . CSF . Blood . Biomarker . Proteomics

Introduction Alzheimer’s disease (AD), a progressive neurodegenerative disease, is the leading cause of mental deterioration among the elderly (60 %), affecting 13 % of people over 65 and almost 50 % of people over 85 years of age (Hebert et al. 2003; Plassman et al. 2007; Choi et al. 2010). The rate at which people between the ages of 65 and 85 are diagnosed with AD doubles every 5 years. Approximately 33.9 million people in the world today are afflicted with AD, and 90 million people are projected to acquire AD by 2053 (Risacher and Saykin 2013; Thies and Bleiler 2011; Barnes and Yaffe 2011). Dementia is one of the clinical symptoms of AD. The Y. Fu : D. Zhao : L. Yang (*) State Key Laboratories for Agrobiotechnology, National Animal Transmissible Spongiform Encephalopathy Laboratory, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China e-mail: [email protected]

pathological abnormalities of this disease include cerebral cortical atrophy, loss of cerebral cortex nerve cells, ventricular enlargement, neuronal decline in the nucleus basalis of Meynert, and scattered neurotic plaques and neurofibrillary tangles (NFTs) (Choi et al. 2010). A new AD diagnostic guideline divides this disease into three phases: the dementia phase (AD dementia due to AD), the symptomatic predementia phase (mild cognitive impairment [MCI] due to AD), and the asymptomatic preclinical phase of AD (Jack et al. 2011). The first two phases are for guiding diagnoses in clinical settings, whereas the third, preclinical phase, is for research purposes only (Zhang and Shi 2013). Mutations in genes related to amyloid precursor protein (APP), presenilin 1 (PS1), and presenilin 2 (PS2) cause the presence of scattered neurotic plaques (Risacher and Saykin 2013). Therapy is more effective at earlier stages of the disease than during stages when obvious cognitive decline appears in patients. Unfortunately, clinical examinations cannot identify preclinical AD or measure cellular and molecular changes in the brains of patients. Moreover, the accuracy of diagnosing the earlier symptomatic stage of AD is limited. Thus, the development of accurate, easy to use, and economical biological markers for early diagnosis of AD has been a long-sought goal for scientists (Fig. 1). Biomarkers are substances that can be measured and evaluated as indicators of normal biological processes, pathogenic processes, or pharmacologic responses to therapeutic intervention (Aronson 2005). Useful biomarkers for AD should have several characteristics, including echoing physiological aging processes, reflecting basic pathophysiological processes of the brain, reacting upon pharmacological intervention, displaying high sensitivity and specificity for AD, and being measurable in noninvasive, easily conducted tests. Many technologies are currently being used to search for fluid biomarkers, including genomics, neuroimaging, epigenomics, transcriptomics, metabolomics, lipidomics, and proteomics

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Fig. 1 Basic procedures for biomarker discovery in Alzheimer’s disease

(Fehlbaum-Beurdeley et al. 2012; Xu et al. 2012; Ishikawa et al. 2013). Most biomarkers can be categorized into three types based on their chemistry: small-molecule biomarkers, protein-based biomarkers, and RNA-based biomarkers. Protein-based biomarkers, especially the aggregation-prone proteins, which lead to AD and associate with oxidative stress or inflammation have been widely studied. This review mainly focuses on proteomic methods for detecting biomarkers for AD (Fig. 2).

The Major Approaches in Proteomics A traditional method for searching for protein-based biomarkers is two-dimensional gel electrophoresis (2-DE). 2DE separates proteins in samples using the differences in their charges and molecular weights. The protein bands can be removed from the gel and analyzed for identification with mass spectrometry (MS). Western blotting, enzyme-linked immunosorbent assays (ELISA), and other methods can then be used to verify the candidates (Hu et al. 2010; Baumann and Meri 2004). Although some proteins have been found to be biomarkers for AD using this methodology, the disadvantages of this approach include that it is time-consuming, offers poor reproducibility, and fails to capture small or hydrophobic proteins, and it is difficult to detect several proteins scattered near the same spot (Gygi et al. 2000). To overcome the limitations inherent in this traditional proteomics approach, quantitative methods have been developed to identify AD biomarkers. Two-dimensional difference gel electrophoresis (2D-DIGE) using fluorescence is a modified 2-DE method. The reproducibility of 2D-DIGE is superior to that of 2-DE. Fluorescent dyes are used to label different protein samples

that are then separated on the same gel (Unlu et al. 1997). Other technologies, such as isobaric tags (iTRAQ) for relative and absolute quantitation and stable isotope labeling by amino acids in cell culture (SILAC), can largely avoid the variations related to the performance and other sample-free factors (Evans et al. 2012; Ong et al. 2002). Although there are several proteomic methods for detecting AD biomarkers, their efficiency is less than satisfactory. For an accurate and early diagnosis of AD, these methods should be combined with others, such as with neuroimaging.

Biomarkers in Cerebrospinal Fluid Cerebrospinal fluid (CSF) is the most prevalent sample used in protein-based biomarker discovery for AD because of its proximity to the brain. CSF is not only connected with the extracellular environment in the brain but is also separated from the peripheral circulation by the blood-CSF barrier. Disease-related proteins or peptides most likely diffuse into CSF, and their abnormal concentrations may reflect pathophysiological processes (Zhang 2007; Irwin et al. 2013). Amyloid-Beta Amyloid-beta (Aβ), the main component in extracellular senile plaques in AD, is a product of the large APP, which is cleaved by secretases. After processing through the amyloidogenic pathway, a peptide of 42 amino acids (Aβ1– 42) is produced and aggregates in the brain. Aβ1–40 and Aβ1– 42 are the major forms of Aβ deposited in the brain. Both improved production and reduced clearance in patients with AD contribute to the abnormally high brain levels of Aβ1–40

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Fig. 2 Relationships among biomarker candidates for diagnosis of Alzheimer’s disease. The extracellular deposition and accumulation of intraneuronal neurofibrillary tangles (tau and p-tau) are the main characteristics of Alzheimer’s disease (AD). An increase in the cleaving enzyme β-secretase 1 (BACE1), a rate-limited enzyme of Aβ, contributes to the upregulation of Aβ. The CSF Aβ levels decrease, probably due to the increased deposition of Aβ. Tau and p-tau constitute the intraneuronal NFTs. Tau is important to neuronal axon function, and the abnormal phosphorylation of tau may lead to the death of neurons. The decrease in Aβ-binding protein inhibits the clearance of Aβ, which is an important factor for Aβ deposition. In addition, ApoA-I, an Aβ-binding protein, reduces the production of Aβ-induced chemokines, such as IL-6. It is also associated with cerebrovascular damage and indirectly causes cell

damage or even cell death. For chaperone proteins, a high concentration of clusterin inhibits and a low concentration of clusterin promotes Aβ production. The production of Aβ is inhibited by α-2M, which is involved in the inflammatory response and in damaging the blood-brain barrier. For cytokines, some have an abnormal expression in AD. Increasing levels of IL-6 increase the production of NTFs. C-reactive protein also influences cerebrovascular damage. The increase in AD7c-NTP combined with cell death is involved in the production of p-tau. Thus, combining the analysis of AD7c-NTP with p-tau will enhance the sensitivity and specificity of the diagnosis of AD. Oxidative stress is another cause of neuronal damage. Carbonylation, an oxidative modification of proteins, is also increased in patients with AD

and Aβ1–42 (Forman et al. 2004; Selkoe 2004; Skovronsky et al. 2006; Shaw et al. 2009). The Aβ measured in CSF is a valuable biomarker of AD. Several investigations found that there was a marked decrease (almost 50 % of control levels) of Aβ in patients with AD (600 pg/ml) was found to be two times higher than that in normal controls (60 pg/ml). To date, studies examining CSF levels of p-tau181, p-tau-199, p-tau-235, p-tau-396, and p-tau-404 have suggested that these markers may provide an early diagnosis of AD (Zetterberg et al. 2010; Blennow 2005). P-tau-231 and p-tau-181 distinguished AD from other diseases, such as FTLD, LBD, VaD, and major depression (Cedazo-Minguez and Winblad 2010; Hampel et al. 2010). Therefore, increased levels of t-tau and p-tau are useful predictors for the progression of MCI to AD and of other NDs to AD. BACE1 The cleaving enzyme β-secretase 1 (BACE1) plays an important role during the production of Aβ and APP. BACE1 begins the cleavage of APP and produces an amyloidogenic C-terminal fragment (C99), releasing soluble APPβ (s APP β). Another key enzyme, -secretase, then cleaves C99, leading to the production of Aβ peptide. Levels of both brain and CSF BACE1 are markedly higher in patients with AD than those in normal patients. The interest in BACE1 as a candidate biomarker for AD has recently increased (Lee et al. 2003; Zetterberg et al. 2008; Hampel and Shen 2009). That the elevation of BACE1 signals an increase in Aβ indicates a possible role for the use of BACE1 as a biomarker for detection of AD at a very early stage.

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chronic inflammation, altered antioxidant function, and accumulation of redox-active metals (Mariani et al. 2005; Pereira et al. 2005; Butterfield 2004). Carbonylation has an important influence on the progress of AD disease, and alterations of the protein oxidation status in CSF may indicate the disease stage. The concentrations and carbonylation of the proteins as determined using 2-DE, MS, and database searches were studied in the CSF of patients with AD who exhibit different extent of cognitive decline. In patients with AD, the protein concentrations of β-trace, transthyretin (TTR) isoforms, and λ chain were markedly decreased compared with those in controls. The λ chain protein demonstrated a higher carbonylation level in patients with AD than that in normal patients (Korolainen et al. 2007). Another study provided evidence that a peptide corresponding to oxidized Aβ1–40 could distinguish LBD from Parkinson’s disease (PD) dementia (Bibl et al. 2006). Studies examining sex-specific differences related to oxidative stress and antioxidant defenses demonstrated that the level of carbonylation of an isoform of vitamin D-binding protein (DBP), apolipoprotein A-I (α-1-AT), in men increased more than that in women (Mendoza-Nunez et al. 2001; Schuessel et al. 2004; Choi et al. 2002). AD7c-NTP The concentration of Alzheimer-associated neuronal thread protein (AD7c-NTP), one of the neuronal thread proteins (NTPs), augmented in cortical neurons, brain tissue extracts, CSF, and urine in the early stage of AD (Ghanbari and Ghanbari 1998; Ghanbari et al. 1998; Munzar et al. 2002). The level of its expression matches the extent of dementia. The level of AD7c-NTP from postmortem CSF of patients with AD was markedly higher than that in controls (De La Monte et al. 1996). An immunoassay-AD7c test was developed to detect AD7c-NTP levels in CSF that was linear to 2.0 ng, with an 89 % sensitivity and 89 % specificity (Ghanbari et al. 1998). The overexpression of AD7c-NTP was correlated with some cell death cascades related to the neurodegeneration in AD and linked with the accumulation of p-tau (de la Monte and Wands 2001). The sensitivity and specificity were much higher when the analysis for AD7cNTP was combined with p-tau than for either of them separately (Kahle et al. 2000). The results of these studies show promise for the early diagnosis of AD and indicate that combining the analysis for several candidates may afford a more sensitive and specific diagnosis.

Carbonylation Levels One of the obvious characteristics of neurodegenerative diseases is an increase in oxidative stress (Mariani et al. 2005). Carbonylation is an irreversible oxidative modification of proteins that is closely associated with the concentration of proteins, calcium dysregulation, mitochondrial malfunction,

Biomarkers in Blood The easy sampling of blood plasma attracts many scientists to search for potential biomarkers in plasma and blood.

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Although several challenges are associated with searching for biomarkers of brain disease in blood, such as the dynamic range of blood proteins and obstacles caused by the bloodbrain barrier, studies analyzing biomarkers in blood are rapidly developing. Searching for blood biomarkers begins with proteins that have been found in CSF, such as Aβ and taurelated proteins, and includes markers of protein aging, cell death, inflammation, and cerebrovascular dysfunctions. Alterations observed for the concentrations of some blood proteins in recent studies have paved the way for early detection of AD.

the activation of the alternative complement pathway (Rodriguez et al. 2004) and is present in plaques in AD (Strohmeyer et al. 2000). Evidence also indicates that the level of CFH in plasma increases significantly in AD but shows no difference in other neurodegenerative disorders (Thambisetty et al. 2008; Zhang et al. 2004). Clusterin functions in the activation of the complement system (Thambisetty et al. 2010), and with further investigation, this pathway may offer meaningful identifying markers for AD.

Aβ

The clearance rate of Aβ declines in patients with AD (Mawuenyega et al. 2010), which is a possible explanation for the deposition of Aβ. In addition, the finding that peripheral injections of anti-Aβ antibodies promote Aβ clearance suggests that peripheral Aβ-binding proteins may participate in the clearance of Aβ (Patton et al. 2006). A decrease in Aβbinding proteins leads to the deposition of brain Aβ and may be a potential biomarker for early AD diagnosis. ApoA-I is one of apolipoproteins, and it has a close relationship with Aβ and other apolipoproteins (Koudinov et al. 1998). Several recent studies found that the concentration of apoA-I decreased in the plasma of patients with AD compared with that in their cohorts (Shih et al. 2014). In addition to enhancing Aβ, apoA-I also protects the cardiovascular system to assist in avoiding AD (Gorelick et al. 2011). It has been demonstrated that overexpression of human apoA-I in AβPP/PS1 transgenic mice improves their learning and memory. ApoA-I also reduces the production of proinflammatory chemokines and cytokines induced by Aβ (Lewis et al. 2010). A new study observed that the level of plasma apoC-III also decreased among nondemented individuals with a family history of AD and in patients with AD (Shih et al. 2014). Taken together, these results indicate that plasma apoA-1 may be a possible biomarker for AD and that a low level of apoCIII implies a high risk of AD. TTR is a binding protein that also protects against Aβ deposition and restricts the formation of senile plaques (Thambisetty et al. 2010). One study found a substantial difference in the TTR levels between slowly and rapidly progressing AD (Perrin et al. 2011). Recent reports indicate that the level of TTR decreases in the CSF of patients with AD (Merched et al. 1998; Puchades et al. 2003; Gloeckner et al. 2008; Hansson et al. 2009). TTR is an AD-specific protein, relative to other diseases having dementia as a symptom, such as FTD and LBD (Hansson et al. 2009; Schultz et al. 2010). In one study, researchers examined the levels of TTR in the plasma of 90 people with late-onset AD and 50 age-matched nondemented controls using immunoblotting and a larger independent cohort (n=270) with ELISA. Compared with those in nondemented controls, TTR levels significantly decreased in those patients with AD showing rapid cognitive

Because the decreased level of CSF Aβ is one of the accepted markers for AD, several studies have also examined plasma Aβ levels. One study showed that the level of plasma Aβ increased in familial AD (Cedazo-Minguez and Winblad 2010). Other studies found that the levels of plasma Aβ1–42 and Aβ1–40 are unstable, observing elevated, reduced, or unchanged levels (Zetterberg et al. 2010; Cedazo-Minguez and Winblad 2010). Compared with normal, age-matched subjects, women with AD have an increased level of Aβ in their blood (Assini et al. 2004). This may be due to Aβ binding to other proteins and becoming trapped or the large amount of Aβ that exists in platelets influencing the plasma levels (Borroni et al. 2010; Tang et al. 2006; Blasko et al. 2005; Colciaghi et al. 2004). Immune-Related Proteins as Potential Biomarkers The systemic immune response is altered in patients with AD. Neuroinflammatory processes, including activation of microglia and expression of proinflammatory cytokines, are chief factors leading to the death of neuronal cells in the brains of patients with AD. Several studies observed a blood-based panel of secreted signaling proteins that distinguished blinded samples from patients with AD and control subjects with high accuracy. One study found that a difference in the relative ratios of 18 plasma biomarkers had the potential to identify patients with AD from controls, including chemokines, cytokines, growth factors, and binding proteins (Ray et al. 2007). Other studies confirmed these biomarkers using sandwich ELISA and Luminex methods. However, the sensitivity and specificity were only 60 and 70 %, respectively (Marksteiner et al. 2011; Soares et al. 2009). It has been reported that the activation of the complement system occurs not only in the brain but also in the blood of patients with AD. A number of complement factors, such as factor Bb and fragments of C3 and C4, changed their expression in the blood of patients with AD (Britschgi and Wyss-Coray 2007). A recent study found that the level of complement factor H (CFH) precursor increased in AD (Hye et al. 2006). CFH is a critical inhibitor of

Aβ-Binding Proteins

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decline or severe cognitive impairments. A regression analysis also suggested that plasma TTR levels declined over 6 months (Velayudhan et al. 2012). Together, these data indicate that TTR is a strong candidate biomarker for the diagnosis of AD and that Aβ-binding proteins may act as markers of disease severity and progression. Chaperone Proteins as Biomarkers for AD The clusterin in the blood of patients with AD correlates with the pathology, severity, and progression of AD as determined using neuroimaging and proteomics: high clusterin levels correlate with a more rapid rate of cognitive decline, a greater severity of AD, and a more marked burden of Aβ in the brain. In normal elderly people, higher concentrations of clusterin are related to a greater propensity to develop dementia. After investigating the expression of clusterin mRNA in blood cells, researchers suggested that the plasma clusterin originates in organs, including the brain and liver (Thambisetty et al. 2010). Clusterin, an extracellular chaperone protein, regulates the formation and clearance of Aβ (Wilson et al. 2008). Another study found that higher clusterin substrate ratios inhibit and lower increased amyloid formation (Yerbury et al. 2007). The amyloid chaperone α-2-macroglobulin (α-2M) inhibits the formation of Aβ (Bauer et al. 1991). It also regulates the immune response (Armstrong and Quigley 2001) induced by inflammatory cytokines (Strauss et al. 1992) and is a marker of damage to the blood-brain barrier (Cucullo et al. 2003). One study found increased levels of α2M in the plasma of AD patients compared with those in controls using 2-DGE-MS analysis and semiquantitative immunoblotting (Hye et al. 2006). Although differences in the CSF clusterin levels between patients with AD and normal controls are inconclusive (Nilselid et al. 2006; Sihlbom et al. 2008), findings indicate that other amyloid chaperone proteins or disease-related chaperones may be related to early pathogenesis and may contribute to the early diagnosis of AD. Potential Inflammatory Biomarkers The role of the immune system in the CNS during the pathogenesis of AD is well accepted. Several cytokines show abnormal concentrations in brains of patients with AD, such as upregulated IL-1 and S100 (Mrak and Griffin 2005). Although several studies have examined potential inflammatory biomarkers in CSF, their results are inconsistent. The expression of IL-6, a proinflammatory cytokine involved in the formation of N-terminal fragments (NTFs), has been shown to increase, decrease, and remain unchanged in the CSF of patients with AD. Similarly, inconsistent results were observed for M-CSF, TNF-α, and TGFβ (Mrak and Griffin 2005). Such paradoxical results may be due to individual

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differences, inconsistent methods, or several other factors. Considering the important role of these cytokines in the pathogenesis of AD, researchers need to establish more accurate methods of determining their expression in AD CSF. Recent studies determined four proteins as candidate biomarkers in AD: ApoE, brain natriuretic peptides (BNP), C-reactive protein, and pancreatic polypeptide (Mrak and Griffin 2005; Hu et al. 2012). C-reactive protein is associated with cerebrovascular damage, which leads to a failure in supplying energy to the brain and silent strokes. Other studies found that natriuretic peptides (NP), a family of peptides that includes atrial NP (ANP) and BNP as well as the larger precursor proteins midregional pro-ANP (MR-pro-ANP) and N-terminal proBNP (NT-pro-BNP), are relevant to the identification of AD (Marksteiner et al. 2014; Kondziella et al. 2009; Nilsson et al. 2006; Ewers et al. 2010).

Conclusion Currently, only three biomarkers, Aβ1–42, tau, and p-tau-181, have been accepted internationally as markers for the diagnosis of AD; however, researchers have still found some proteins with great value for AD diagnosis. A study using 2D-PAGE to analyze CSF samples from patients with mild AD and cognitively normal controls found that by combining Aβ42 and tau with four proteins, NrCAM, YKL-40, chromgranin A, and carnosinase1, the accuracy of diagnosis was increased and six stages of AD could be defined: non-AD, preclinical AD, period of risk (including three subperiods), and mild dementia. Aβ deposition correlates with abnormalities in the functions of the ubiquitin-proteasome pathway (Perrin et al. 2011). The ubiquitin levels are markedly increased in the cerebral cortex and CSF of patients with AD (Ponnappan 2002; Wang et al. 1991). A recent study showed that the conjugating and activating enzymes E1 and E2 were altered in the blood of patients with AD. The senescence marker p53 also identifies AD, differentiating patients with AD from normal controls by its unusual and remarkable conformational state (Lanni et al. 2007). One plausible explanation for the cellular abnormality observed in AD is cellular senescence due to the stress response (Baird 2006). Based on all the above studies, we can expect to find biomarkers for neurodegenerative diseases in some disease-specific proteins, such as Aβ for AD, PrP for prions, α-synuclein for PD, and polyglutamine-containing proteins for HD, as well as in disease-related proteins, such as enzymes involved in AD, chaperones of Aβ, proteins in complement pathways and cell death or senility, and cytokines associated with inflammation and other disease processes. Cerebrospinal fluid, blood, plasma, serum, urine, and saliva may be sources of biomarkers in AD, similar, for example, to

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the level of 8-hydroxydeoxygyanosine (8-OHdG) in urine correlating with the stage of PD. Although many studies have found several candidate biomarkers for AD, numerous obstacles inhibit the discovery of sensitive, specific, and easily accessible biomarkers to diagnose and monitor AD progression. A summary of the main hindrances follows. 1. Sample processing Sample preparation is a crucial step in proteomics. For example, repeated freeze-thaw cycles or storing samples at room or high temperatures will negatively influence experimental success. Using different types or doses of anticoagulations when obtaining blood samples leads to variable results for the same protein. 2. Economics and efficiency of analytical methods To date, all diagnostic biomarkers are in the testing stage, with no broad use of commercial kits. Currently, ELISAs for detecting Aβ, t-tau, and p-tau cost €68 per patient (Humpel 2011). In addition to the poor repeatability of 2-DE, proteomic analyses are time-consuming. Thus, cheaper and more convenient examinations are required. 3. Data interpretation and diagnostic criteria Even with a laboratory background, many physicians cannot interpret raw data. Therefore, internationally standardized criteria for data interpretation and diagnostic guidelines are essential. 4. Appropriate controls During the discovery phase, researchers must incorporate samples from controls that have been properly matched for age, lifestyle, sex, and education. During the validation phase, the samples obtained must be large enough to examine for other clinically relevant diseases.Taking all these limitations into consideration indicates that it is a long journey toward the application of proteins as diagnostic biomarkers for AD. Due to the difficulty of obtaining biopsy samples in neurodegenerative diseases, the combination of many types of information may increase the specificity of the diagnosis and will be the trend in early diagnosis, including uniting the analysis of several proteins or miRNAs, as well as integrating neuroimaging methods with proteomics, genomics, epigenomics, transcriptomics, metabolomics, and lipidomics. Such methods may provide a future that conquers Alzheimer’s disease and other neurodegenerative diseases.

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